Columnar stores bring notable benefits for analytic workloads where data is loaded in batchesOpen source columnar store extension for PostgreSQL and share it
with the community! Columnar stores bring notable benefits for analytic
workloads, where data is loaded in batches.This columnar store extension uses the Optimized Row Columnar (ORC)
format for its data layout. ORC improves upon the RCFile format
developed at Facebook, and brings the following benefits:

Compression: Reduces in-memory and on-disk data size by 2-4x. Can be extended to support different codecs.

Skip indexes: Stores min/max statistics for row groups, and uses them to skip over unrelated rows.

Further, we used the Postgres foreign data wrapper APIs and type representations with this extension. This brings:

Support for 40+ Postgres data types. The user can also create new types and use them.

Statistics collection. PostgreSQL's query optimizer uses these stats to evaluate different query plans and pick the best one.

Simple setup. Create foreign table and copy data. Run SQL.

It's worth noting that the columnar store extension is
self-contained. If you're a PostgreSQL user, you can get the entire
source code and build using the instructions on our GitHub page (link is external). You can even join columnar store and regular Postgres tables in the same SQL query.

The objective of this project is to apply various NLP sentiment analysis techniques on reviews of the Yelp Dataset and assess their effectivenes on correctly identifiyng them as positive or negativeComparison